The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle collisions at the LHC. This new approach can reconstruct collisions more quickly ...

A machine learning algorithm used gene expression profiles of patients with gout to predict flares. The PyTorch neural network performed best, with an area under the curve of 65%. The PyTorch model ...

An artificial-intelligence algorithm that discovers its own way to learn achieves state-of-the-art performance, including on some tasks it had never encountered before. Joel Lehman is at Lila Sciences ...

This repository implements the main experiments of our paper, Distilling Many-Shot In-Context Learning into a Cheat Sheet (EMNLP 2025 Findings). We introduce cheat-sheet ICL, which distills the ...

On ESPN Fantasy, Josh Allen and Lamar Jackson are the top two signal-callers, but we’re projecting second-year sensation Jayden Daniels to finish as the QB1 in 2025. The Commanders bolstered his ...

Patent applications on artificial intelligence and machine learning have soared in recent years, yet legal guidance on the patentability of AI and machine learning algorithms remains scarce. The US ...

Diabetic peripheral neuropathy (DPN) is a common and debilitating complication of type 2 diabetes mellitus (T2DM), significantly impacting patients’ quality of life and increasing healthcare burdens.

This paper presents a new snow parameter retrieval (SPR) algorithm for the Global Change Observation Mission-Climate/Second Generation Global Imager (GCOM-C/SGLI) instrument (2018-present). This ...

Researchers from MIT, Microsoft, and Google have introduced a “periodic table of machine learning” that stands to unify many different machine learning techniques using a single framework. Their ...

Recent technological advancements have enabled clinicians to integrate data into predictive models, potentially transforming early diagnosis in neonatology. Using predictive models to detect neonatal ...

Abstract: Securing systems, networks, and information amid cyber threats involves a blend of machine learning and cybersecurity, which uses machine learning to identify abnormal behaviors, classify ...